Data Fabric A data fabric enables frictionless access and sharing of data in a distributed data environment. It enables a single and consistent data management framework, which allows seamless data access and processing by design across otherwise siloed storage. It may use analytics to constantly monitor data pipelines and support the design, deployment, and utilization of diverse data. Gartner® Data and Analysis Trends, 2021 (see References) claim that this can reduce time for integration by 30%, deployment by 30%, and maintenance by 70%. A data fabric has an application interface, and often also a user interface. It gives the ability to write data, as well as to read it. The sources may be on-premise or in the cloud. Data fabrics deliver a unified, intelligent, and integrated end-to-end platform to support data use-cases. They provide the ability to deliver use-cases quickly by leveraging innovation in dynamic integration, distributed, and multi-cloud architectures, graph engines, and distributed in-memory and persistent memory platforms. Data fabric focuses on automating the process integration, transformation, preparation, curation, security, governance, and orchestration to enable analytics and insights quickly for business success. It minimizes complexity by automating processes, workflows, and pipelines, generating code, and streamlining data to accelerate various use-cases. An application can read data from or update data in multiple sources, describing the data in terms of a common data model. The read and update requests are converted by data platforms to requests that describe the data in terms of the source data models. The data is then obtained from the sources and integrated, or updated in the sources, by continual synchronization or dynamic query.